effect). Sales and output multipliers tend to be around the double of income multipliers(Heng and Low, 1990).126.96.36.199Multipliers and features of destination regionThe value of the multipliers crucially depends on leakages, and therefore on the share ofimports on total output. In turn, the share of import is heavily dependent on the size of theregion (small economies are relatively less self-contained than larger economy). In thespecific case of tourism multipliers, the interrelationships of tourism industries with therest of the local economy (and specifically the extent to which demand from tourismindustries is satisfied with imports), is also a crucial factor.Income multipliers reach a maximum for large countries such as Turkey and the UK(Fletcher, 1989) and in self-contained small island economies (Jamaica, Mauritius),where they vary in the range 0.50-1.20. They are just smaller for US states (range 0.40-0.90 – Archer, 1988), but sensibly lower in very open regional and urban economies suchas US and UK counties (range 0.20-0.50 – Fletcher, 1989; Archer, 1982). Baaijenset al(1998) analyzed statistically (regression models) income multipliers extracted from 11studies. A positive relationship was found with the logarithm of the population (severalalternative regional characteristics - as area size, number of tourist arrivals - were alsotested). A similar result was found by Chang (2001), analyzing more than 100 regionalIOmodelsvaryinginsizeandeconomicdevelopment(coveringfiveUS-states:California, Colorado, Florida, Michigan and Massachusetts), generated by means of theIMPLAN IO modelling system. A ‘tourism multiplier’ was defined as a weighted sum ofmultipliers derived from four tourism related sectors (lodging, eating and drinking,recreation and retail). For all the four analyzed Type II ‘tourism multipliers’ (sales,income, value added and job) the most significant predictor, in a stepwise regressionanalysis, was found to be the logarithm of population. While sales, income and valueadded multipliers increased almost linearly with the logarithm of population, theemployment multiplier showed a negative correlation (interpreted on the basis that, in thecontest of the analyzed dataset, regions characterized by a smaller number of inhabitantstend to correspond to less economic developed rural areas). Using hotels as an example,higher job to sales ratio could be a result of lower room rates, or more part time andseasonal jobs (resulting in lower average wages).
24Figure 1: distribution of income (left) and of employment (jobs per million dollars in sales, right)Type II multipliers vs. Log (Population) for 114 US regions. The empty blue diamonds report theresults obtained through IO modelling (IMPLAN), while the magenta squares correspond to thecorresponding results from a statistical regression analysis, with Log (Population) as dominantpredictors. In brown are also reported empirical multipliers proposed from a straightforwardclassification of the different regions in ‘rural’, ‘small metro’, ‘large metro’ and ‘State’ (Chang,2001)188.8.131.52